Quantification of spatial patterns is a useful tool in the natural sciences including geology. While fractal mathematics may be helpful in describing naturally occurring structures, the complexity of such mathematical approaches can lead to more, rather than less complex descriptions. In this regard, the concept of lacunarity has been found to be useful for describing spatial distributions of data sets, including those having clustered, random, fractal and multifractal distributions. Lacunarity allows for statistical investigation of binary and/or continuous data sets and is applicable to data of any dimensionality.
In a particular application, in evaluating the potential value of a newly identified reservoir or the potential value of capital projects within an existing developed reservoir, it may be useful to quantify the heterogeneity of a region of interest. In particular, such quantification may be used to evaluate and interpret patterns in stratigraphy including cyclicity of bed properties and connectivity of depositional bodies. Moreover, quantification of heterogeneity may be used to classify analog datasets, perform data/model comparisons, make flow assessments, and make predictions at scales below observable scales.